The present embodiments relate to detection of a probe in fluoroscopy. 2D X-ray fluoroscopy is routinely used for interventional cardiac surgery. X-Ray fluoroscopy and transesophageal echocardiography (TEE) provide complementary information during the cardiac surgery. Fluoroscopy is used to monitor interventional devices (e.g., catheter and TEE probe), and 3D TEE is used to visualize soft tissue. To fully utilize complementary fused information from both modalities, the coordinate systems of the fluoroscopy and ultrasound are registered or aligned.
In one approach to align the coordinate systems, a learning-based detection finds a transform between the coordinate systems based on detection of a pose of the probe in a fluoroscopy image. The pose of the probe is separated into the in-plane and out-of-plane parameters. The in-plane parameters are computed from the probe's position, size, and orientation. Out-of-plane parameters are computed with template matching. In practice, single frame-based detection may have low accuracy due to probe appearance ambiguity in a given fluoroscopic image, low X-Ray dose, noise, and/or clutter.